// ai_consulting
Practical AI, minus the hype.
AI can take real work off your team’s plate, but only when it’s pointed at the right problems. We help small and mid-sized businesses find those problems, test a fix on a small scale, and build what works into everyday tools.
// where_ai_helps
Where AI actually helps.
Most of the value is in ordinary, repetitive work, not in flashy demos.
Process improvement
Find the repetitive steps in how work gets done, and decide which ones AI can speed up and which should stay human.
Internal tools
Assistants and tools built around your own documents, data, and processes, not a generic chatbot.
Content assistance
First drafts of emails, descriptions, and posts that your team edits for voice and accuracy.
Support workflows
Answer routine customer questions and route the rest to the right person, with a human in the loop.
Automation planning
Map which tasks to automate first, what each one costs, and how you’ll know it worked.
AI features in your apps
Generative and agentic features added to websites and custom software where they genuinely help.
// where_to_draw_the_line
What AI shouldn’t do.
Knowing where not to use AI matters as much as knowing where to use it.
Good fits
Keep it human
For examples that work, read practical AI use cases for small businesses.
// why_hess_webtech
Practical, responsible, and proven.
Practical first
We start from your workflows, not from a tool we want to sell, and we’ll tell you when a simple non-AI fix is the better answer.
Responsible by default
Clear rules about data, a person reviewing what matters, and results measured before anything scales.
We ship it
Our own app, Tericipe, uses AI to read handwritten recipe cards and flags lines it isn’t sure about instead of guessing.
// how_it_starts
Start small. Prove it. Then scale.
Every engagement starts with an assessment and a single pilot, so you see real results before committing to more.
Assess
We look at how work actually gets done and list where AI could help, with rough costs and risks for each.
Pick a pilot
Choose one measurable workflow to try first, small enough to finish quickly.
Run it
Build and run the pilot with your team, keeping a person in the loop and tracking results.
Decide & scale
Keep what works, drop what doesn’t, and plan the next step from real results.
// faq
Questions we hear a lot.
Do we need to be technical to use AI?
No. We start from how your team works today and explain the options in plain language.
Will AI replace our staff?
That’s not the goal. A good pilot takes repetitive work off people’s plates so they can spend more time on work that needs judgment.
What about our data and privacy?
We set clear rules about what data each tool can see, and keep sensitive information out of tools that aren’t approved for it.
Which AI tools do you use?
Whatever fits the job and your existing systems. We’re not tied to one vendor, and we’ll tell you when a simple non-AI fix is the better answer.
How much does an AI assessment cost?
It’s scoped to the size of your team and the workflows involved. You’ll get a clear proposal before any work starts.
How do we know if a pilot worked?
Before the pilot starts, we agree on what to measure, like hours saved, response time, or error rate, and review the results together at the end.
// further_reading